NUMPY IN PYTHON

NUMPY IN PYTHON:-

INTRODUCTION OF NUMPY:-

1. NumPy is a Python Package And Its Stand For Numerical Python.
2. Provide Lot Of Functions To Work In a Domain Of Linear Algebra And Matrix.
3. Provide Functions Related To Arrays.
4. Create An Array Called ndarray.
5. Working Of ndarray is Faster Than List.
6. Get The Version Of NumPy Print(NumPy……Version…)
7. Most Of The Part Of NumPy Create In C And C++.

CREATES OF NDARRAY:-

• We Have To Use Array() — ->List/Tuple.
• Import Numpy as np.
• Where (as) Stands For ALIAS NAME/ALTERNATE NAME .

TYPES OF ARRAYS:-

• 0-Dimensional Array
• 1-Dimensional Array
• 2-Dimensional Array
• 3-Dimensional Array

ATTRIBUTES & METHODS:-

• Shape:-Returns The Shape Of The Array.
• Size:-Returns Total No Of Elements In An Arrays.
• Shape=() :-For Permanent Changes Of Arrays.
• Transpose:- Converts Rows Into Columns And Columns Into Rows.
• Reshape():- Used To Change The Shape Of An Array. But It Will Change Temporary.

JOINING ARRAYS IN NUMPY:-

1. Concatenate.
2. Stack.
3. vstack.
4. hstack.
5. Append.

FUNCTION IN NUMPY:-

1. Arange().
2. Linspace().
3. Logspace()

SLICING OPERATION ON NDARRAY IN NUMPY: -

NUMPY ARRAY CREATION ROUTINE:-

1. Empty
2. Zeros
3. Ones
4. Eye

NUMPY-ARRAY SELECTION:-

STATISTICAL FUNCTIONS:-

1. a min() = Minimum Element.
2. a max() = Maximum Element.
3. average() = Average.
4. mean() = Mean.
5. median() = Median.
6. var() = Variance.
7. std() = Standard Deviation.

ARITHMETIC OPERATION:-

1. ADDITION
2. SUBSTRACTION
3. MULTIPLICATION
4. DIVISION
5. MODULO
6. POWER
7. RECIPROCAL
8. COMPLEX NUMBER

RULES FOR IMPLEMENTING ARITHMETIC OPERATION (BROADCAST RULES)

1. Shape Of Two Arrays Must Be Equal.
2. Second Array Should Have At least One Dimension And The Number Of Element In That Dimension Should be Equal To First Array.
3. Second Array Having Single Element.